netmeta: Network Meta-Analysis using Frequentist Methods
Official Git repository of R package netmeta
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Authors
Gerta Rücker,
Ulrike Krahn,
Jochem König,
Orestis Efthimiou,
Annabel Davies,
Theodoros Papakonstantinou,
Guido Schwarzer
Description
R package netmeta (Balduzzi et al., 2023) provides frequentist methods for network meta-analysis and supports Schwarzer et al. (2015), Chapter 8 "Network Meta-Analysis".
Available network meta-analysis models
Methods to present results of a network meta-analysis
-
network graphs (Rücker & Schwarzer,
2016);
-
forest plots;
-
league tables with network meta-analysis results;
-
tables with network, direct and indirect estimates looking similar to the statistical part of a GRADE table for a network meta-analysis (Puhan et al., 2014).
Methods to rank treatments
Methods to evaluate network inconsistency
Additional methods
Installation
Current official
release:
install.packages("netmeta")
Current
release on GitHub:
Installation using R package
remotes:
install.packages("remotes")
remotes::install_github("guido-s/netmeta")
How to cite netmeta?
Balduzzi S, Rücker G, Nikolakopoulou A, Papakonstantinou T, Salanti G, Efthimiou O, Schwarzer G (2023): netmeta: An R package for network meta-analysis using frequentist methods. Journal of Statistical Software, 106, 1-40
A BibTeX entry for LaTeX users is provided by
citation(package = "netmeta")
Bug Reports:
You can report bugs on GitHub under
Issues.
or using the R command
bug.report(package = "netmeta")
(which is not supported in RStudio).
References
Balduzzi S, Rücker G, Nikolakopoulou A, Papakonstantinou T, Salanti G, Efthimiou O, Schwarzer G (2023): netmeta: An R package for network meta-analysis using frequentist methods. Journal of Statistical Software, 106, 1-40
Carlsen L, Bruggemann R (2014): Partial order methodology: a valuable tool in chemometrics. Journal of Chemometrics, 28, 226-34
Chaimani A, Salanti G (2012): Using network meta-analysis to evaluate the existence of small-study effects in a network of interventions. Research Synthesis Methods, 3, 161-76
Davies AL, Papakonstantinou T, Nikolakopoulou A, Rücker G, Galla T (2022): Network meta-analysis and random walks. Statistics in Medicine, 41, 2091-2114
Dias S, Welton NJ, Caldwell DM, Ades AE (2010): Checking consistency in mixed treatment comparison meta-analysis. Statistics in Medicine, 29, 932-44
Efthimiou O, Rücker G, Schwarzer G, Higgins J, Egger M, Salanti G
(2019): A Mantel-Haenszel model for network meta-analysis of rare
events. Statistics in Medicine, 1-21
König J, Krahn U, Binder H (2013): Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons. Statistics in Medicine, 32, 5414-29
Krahn U, Binder H, König J (2013): A graphical tool for locating inconsistency in network meta-analyses. BMC Medical Research Methodology, 13, 35
Papakonstantinou T, Nikolakopoulou A, Rücker G, Chaimani A, Schwarzer G, Egger M, Salanti G (2018): Estimating the contribution of studies in network meta-analysis: paths, flows and streams. F1000Research, 7, 610
Puhan MA, Schünemann HJ, Murad MH, Li T, Brignardello-Petersen R, Singh JA, Kessels AG, Guyatt GH, for the GRADE Working Group (2014): A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ, 349, g5630)
Rücker G (2012): Network meta-analysis, electrical networks and graph theory. Research Synthesis Methods, 3, 312-24
Rücker G, Schwarzer G (2014): Reduce dimension or reduce weights? Comparing two approaches to multi-arm studies in network meta-analysis. Statistics in Medicine, 33, 4353-69
Rücker G, Schwarzer G (2015): Ranking treatments in frequentist network meta-analysis works without resampling methods. BMC Medical Research Methodology, 15, 58
Rücker G, Schwarzer G (2016): Automated drawing of network plots in network meta-analysis. Research Synthesis Methods, 7, 94-107
Rücker G, Schwarzer G (2017): Resolve conflicting rankings of outcomes in network meta-analysis: Partial ordering of treatments. Research Synthesis Methods, 8, 526-36
Rücker G, Petropoulou M, Schwarzer G (2020): Network meta-analysis of multicomponent interventions. Biometrical Journal, 62, 808-21
Rücker G, Nikolakopoulou A, Papakonstantinou T, Salanti G, Riley RD, Schwarzer G (2020): The statistical importance of a study for a network meta-analysis estimate. BMC Medical Research Methodology, 20, 190
Salanti G, Ades AE, Ioannidis JPA (2011): Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. Journal of Clinical Epidemiology, 64, 163-71
Schwarzer G, Carpenter JR and Rücker G (2015): Meta-Analysis with R (Use R!). Springer International Publishing, Switzerland